Asad Rokhzadi

Due to the increasing importance of using environmentally friendly methods to increase the yield of crops, two- year experiment carried out in a field located in the Dehgolan region, in the northwest of Iran, to study influence of sulfur spraying and plant growth promoting rhizobacteria inoculation on canola traits. The experiment was arranged as a split-plot factorial arrangement based on randomized complete block design with three replications. The main plots included two levels of sulfur (control and application), and the factorial combinations of strigolactone (control and application) and microorganisms (control, Funneliformis mosseae, Bacillus lentus, Pseudomonas fluorescens, Thiobacillus sp.) were allocated to the sub-plots. The results of combined analysis showed that the 1000 seed weights and seed yield increased significantly by sulfur application. At the same time, the 1000 seed weights decreased under the influence of strigolactone. Also, the SPAD number, the number of pods and seeds per plant, the 1000 seed weights and the seed yield increased significantly by influence of microorganisms, especially Thiobacillus, compared to control treatment. Based on the results of interaction effects, all traits except the number of SPAD were affected by the interaction effect of sulfur, strigolactone and microorganisms. The application of sulfur along with strigolactone and Thiobacillus significantly increased the number of pods per plant (200), the 1000 seed weights (4.53 g) and the seed yield (2552 kg/ha).

The study aimed to optimize the rate of nitrogen (N), phosphorus (P), and zinc (Zn) fertilization in dryland chickpea. A 2‐year study was conducted to analyze the chickpea responses to N (0, 25, and 50 kg ha ⁻¹ ), P ₂ O ₅ (0, 30, and 60 kg ha ⁻¹ ), and Zn (0, 10, and 20 kg ha ⁻¹ ) using the response surface methodology (RSM) technique. The optimization of fertilizer application was conducted using three approaches: economic, environmental, and economic‐environmental (integrated). There was more and better‐distributed precipitation in the first year compared to the second year. Increasing the N rate in the first year improved seed yield and increased the content of protein, phosphorus, and zinc in seeds, while the crop's response to N in the second year was lower. Phosphorus improved seed yield in the first year but had no effect on it in the second year. Zn positively affected seed yield in both years. Comparing the optimization methods indicated that the integrated approach was most successful. This approach decreased fertilizer usage significantly compared to the economic approach and resulted in higher seed yield than the environmental approach. According to the integrated approach, the optimal amounts of N, P ₂ O ₅ , and Zn to be used were 26, 16, and 8 kg ha ⁻¹ , respectively, in the high rainfall year, and 13, 0, and 4 kg ha ⁻¹ in the low rainfall year. The findings indicated that by incorporating economic and environmental considerations, a low‐input fertilization strategy could be implemented to achieve satisfactory yields in chickpea dryland farming.

Camelina [Camelina sativa (L.) Crantz] is an annual versatile oilseed crop of the Brassicaceae family, with an increasingly cultivated area. Predicting camelina seed yield response to fertilization and planting density is of great importance in understanding production potential and management planning. Therefore, the current study aimed to estimate the seed yield of camelina by response surface methodology (RSM) and artificial neural network (ANN) as affected by different levels of planting row spacing and nitrogen (N), sulfur (S), and cow manure (CM) fertilization. The experiment was conducted in two growing years of 2019–2020 and 2020–2021, based on a central composite design with four factors including row spacing (15–35 cm), N (0–200 kg ha⁻¹), S (0–100 kg ha⁻¹), and CM (0–40 t ha⁻¹). The RSM models for seed yield versus fertilization and row spacing factors in both years were statistically significant and had an acceptable predictive ability. Camelina seed yield decreased with increasing row spacing but showed a positive response to increasing the amount of N, S, and CM fertilizers. Comparing the performance of the models showed that, although the RSM models were significant and had the necessary efficiency in predicting camelina seed yield, the ANN models were more accurate. The performance criteria of coefficient of determination (R²), root mean square error (RMSE), standard error of prediction (SEP), mean absolute error (MAE), and Akaike information criterion (AICc) averaged over the two years for the RSM model were 0.924, 51.60, 5.51, 41.14, and 394.05, respectively, and for the ANN model were 0.968, 32.62, 3.54, 19.55, and 351.33, respectively. Based on the results, the ANN modeling can be used in predicting camelina seed yield in field conditions with more confidence than the RSM technique.

Nutrient management has a decisive impact on the biomass and essential oil yield of medicinal plants. This study aimed to determine the optimal levels of nitrogen, potassium, and seaweed extract fertilizers to maximize the yield and quality of thyme using the response surface methodology (RSM). The experiment was laid out as a Box-Behnken design with three replications and three experimental factors, including nitrogen (urea) (0, 200, and 400 kg ha⁻¹), and foliar application of potassium (Flourish Sulfopotash) (0, 6, and 12 kg ha⁻¹) and seaweed extract (0, 3, and 6 L ha⁻¹⁾. The generated models were statistically significant for all measured traits except for γ-terpinene and p-cymene. While the influence of N on the amount of photosynthetic pigments followed a quadratic trend, the response of total chlorophyll and carotenoids to increasing potassium was linear. The response of biomass yield to N and seaweed was quadratic and linear, respectively. Potassium application had no significant influence on biomass. Essential oil yield reached its peak value (12 kg ha⁻¹) when N and seaweed were applied at their intermediate levels and with the maximum application rate of potassium. Thymol was identified as the highest essential oil component (46.1%), followed by γ-terpinene (19.2%), p-cymene (14.1%), and carvacrol (5.6%). The optimization results suggested that the application of 162 kg ha⁻¹ urea, 12 kg ha⁻¹ Flourish Sulfopotash, and 4 L ha⁻¹ seaweed extract was sufficient to produce the maximum dry matter (1247 kg ha⁻¹), and more than 11 kg ha⁻¹ of essential oil, with a concentration of 1%. Through optimization, the amounts of thymol and carvacrol were estimated to be as much as 44.2% and 6.2%, respectively. The results of the study suggested that resource optimization through RSM can be used as an efficient method to manage the consumption of fertilizers in thyme production.

Ameliorating effects of exogenous paclobutrazol and putrescine on mung bean [Vigna radiata (L.) Wilczek] under water deficit stress | Esmaeil Babarashi, Asad Rokhzadi, Babak Pasari, Khosro Mohammadi | Agricultural Journals

Introducing optimum ranges of agronomic resources such as fertilizers and plant materials is of great importance in crop production systems. In this study response surface methodology (RSM) was used for empirical modeling and optimizing the effects of plant density, nitrogen (N) and micronutrients (M) fertilizers on dry matter yield, essential oil production and nitrogen use efficiency (NUE) of sage (Salvia officinalis L.). The experimental factors of plant density (5–10 plants m⁻²), N (0–200 kg ha⁻¹) and M (0–4 g L⁻¹) fertilizers were laid out in a Box-Behnken design. Increasing plant density under high rates of M fertilizer resulted in increased dry matter, essential oil and NUE while plant density without M fertilizer application, had no effect. The simultaneous application of N and M fertilizers had a synergistic effect on dry matter yield and essential oil production. In general NUE decreased with increasing the rate of N fertilizer. Through optimization operation the density range of 8.7–10 plants m⁻², the N fertilizer rate less than 95 kg ha⁻¹ and the M fertilizer range of 2.4–4 g L⁻¹ were suggested as the optimum conditions to obtain desirable values of responses.

Adopting an appropriate planting method and application of soil amendments such as zeolite in dryland conditions could be highly effective in improving growth and productivity of crop plants. Therefore the response of two chickpea (Cicer arietinum L.) genotypes (Azad and Adel) to two planting methods (flat and furrow patterns) and different rates of zeolite (0, 10 and 20 t ha-1) was examined in a field study under dryland conditions. Zeolite application increased plant height, pods number/plant and seed yield, under flat planting pattern, while in furrow pattern, chickpea yield decreased with the application of zeolite. Under no zeolite condition, sowing in furrows improved plant height and pods number compared with flat sowing. Zeolite had no effect on Azad cultivar, but the pods number/plant of Adel was significantly increased by applying 20 t ha-1 zeolite compared with control. In general, the best result in terms of crop growth and yield was obtained from applying 20 t ha-1 zeolite in flat planting pattern. Positive response of the plant to zeolite application in flat planting pattern and, on the other hand, the yield reduction resulting from zeolite addition in furrow planting condition suggested that the influence of zeolite on the crop was dependent on planting method.